AI-powered talent network and data provider to frontier AI labs.
- Data beyond brokerage
- The State of Startups in 2026
- Rethinking Legacy Data Infrastructure with Eon Co-Founders Ofir Ehrlich and Gonen Stein
- AI Frenzy Brings Dual Valuation Deals into the Mainstream
- The data black hole at the center of AI
- OpenAI Files (Not So) Confidentially to Go Public
- Brendan Foody (Mercor) — Agentic Data and the Future of AI
- SpaceX Aims for a $1.75B Valuation, with Pricing Set for June 11th
- Adarsh Hiremath (Mercor CTO) — Felicis Fireside
“Those type of companies are looking for large-scale, generated generic datasets to sell at scale to many other providers.”
Source→“Mercor, Harvey — Referenced in context of application-layer AI company strength”
Source→“Mercor and Surge — Data-labeling/data-economy companies cited as potentially becoming enormous businesses (~$200B)”
Source→“Mercor — Followed Scale into the data-for-labs category”
Source→“Harry references investing at $2–3 billion and regretting not following on at $20 billion... data companies with clear AI vision are worth significantly more than investors price them.”
Source→“The rumor, too, is that the other bidder on the data set was Mercor, right, in terms of the bankruptcy bid process. And so it's interesting — you had multiple different companies in the AI world bidding on a bankrupt airline's enterprise data set.”
Source→“Real-world enterprise data is so scarce and valuable for training agents that companies are buying it out of bankruptcy proceedings — a trend expected to accelerate significantly.”
Source→“Mercor: AI data labeling/training data company raising at a $20B valuation led by General Catalyst, with NVIDIA reportedly participating significantly.”
Source→“Brendan Foody, CEO of the AI-training startup Mercor, stirred the pot on the issue on X last month, writing: 'in the last 6 mo's ive seen a half dozen rounds where sequoia invests in 2 tranches. everyone pretends they only did the higher valuation,' and calling the tactic 'deceptive.'”
Source→“Brendan Foody, CEO of the AI-training startup Mercor, stirred the pot on the issue on X last month.”
Source→“"Open source models just raise the floor of what people are interested in. As long as customers still have new capabilities that they want to get better at, our business still continues to grow."”
Source→“I just listened to his podcast with Harry Stebbings, and I was really surprised about the positive things that are going on there... He cleared a lot of air.”
Source→“Mercor: AI-powered hiring and talent marketplace - Named as an Applied Compute customer”
“If you want some intuition, I recommend checking out the job descriptions on Mercor or Serge's websites. There are listings for word specialists who will convert legacy documents into polished word files, and legal experts who will write realistic M&A diligences or securities filings, and management consultants who will write up template market research.”
Source→“Expert Data Is the Scarce Input — Hiring for It Is a Strategic Moat. For any company building AI products that require specialized domain performance (legal, financial, medical, technical), the binding constraint is not compute but access to genuine human expert trajectories.”
Source→“That's what Mercore and a lot of the out-of-data companies are doing. Like, a lot of the jobs for them is to say, well, what are the blind spots for LLMs?”
Source→“in the last 6 [months] ive seen a half dozen rounds where sequoia invests in 2 tranches. everyone pretends they only did the higher valuation. founders misrepresent this to their employees & then shop it to angels too.”
Source→“Reached $1B annualized revenue in ~20 months, currently valued at $10B”
Source→“Mercor CEO Brendan Foody disclosed that his company 'already spends more on AI tokens for internal agents than on employee salaries, a pattern he predicts will spread across corporate America as companies deploy AI agents across more business functions.'”
Source→“We built Apex with that purpose and it's become an industry standard for how labs determine whether their models do well at capabilities enterprises care about.”
Source→“There was an enormous transition happening in the human data market, shifting away from the crowdsourcing paradigm that companies like Scale AI pioneered — low-and-medium-skilled people writing barely grammatically correct sentences for early ChatGPT — toward the agentic data paradigm.”
Source→“If I had to distill what we did strategically into one thing, it's focusing on leading indicators when markets move really fast. The cutting-edge frontier labs see things in the markets where we can learn how the entire economy will change shape.”
Source→“Scale grew up in autonomous-vehicle labeling with people in the Philippines, and infrastructure was built around that. Going directly to the labs, we could build from the ground up around exceptional people creating the new agentic-data paradigm.”
Source→“Mercor might not exist without Prod. All our initial customers were Prod teams — Ben (founding CEO of Anysphere), Cofactory, Rob and Gavin from Etched, and others.”
Source→“The Thiel Fellowship came in March 2024 when the company was at ~$2M revenue... Largest value-add: the credibility stamp to investors and hires, and the community (met Yash, CEO of Applied Compute, previously our customer at OpenAI).”
Source→“We've expanded our relationships with all of the Frontier Labs and added $300 million in net new ARR in the last 60 days.”
Source→“We have an AI project manager that just completed its first project, managing that entire thing end to end, where it's able to hire the experts. It's able to answer their questions. It's able to build the annotation tool using its coding tools within our platform and produce the end data type.”
Source→“Edward Hu, the first author on LoRA, who was previously at OpenAI, is working with us.”
Source→“We've been building out an incredibly strong research team like Edward Hu, the first author on LoRA, who was previously at OpenAI, is working with us.”
Source→“Building defensibility in the software layer on top of the models is going to be incredibly difficult. I think over the last two years, everyone has increasingly realized that the model is the product.”
Source→“Victor got super excited...he said, 'Oh, have you ever been in a helicopter?' And so Peter took us on the helicopter flight. And Benchmark really wanted to work with us.”
Source→“dropped out of Harvard after sophomore year, co-founded Mercor at 19”
Source→“You guys have an incredible benchmark that you put out there, Apex benchmark, where you show that the task of a management consultant”
Source→“You famously were one of the fastest growing companies of all time and gone from zero to 500 million of revenue with just 30, 40 people.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.